Home / gke-labs / kube-agents · agents/cluster/skills/gke-workload-troubleshooting/SKILL.md · GitHub

gke-workload-troubleshooting skillA

gke-workload-troubleshooting is agent-read markdown (skill) from gke-labs/kube-agents: Systematic Standard Operating Procedure (SOP) for diagnosing GKE workload failures, crash loops, resource OOMs, mounting errors, and connectivity timeouts..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# GKE Workload Troubleshooting Skill

Use this skill to systematically diagnose and resolve failures in application workloads deployed in GKE clusters. This skill enforces a read-only diagnostics boundary before proposing manifest or config corrections.

## 🔍 Diagnostic Workflow

### Step 0: Context Acquisition & Time Window Definition

To begin troubleshooting, acquire the following context from the user or active `SETTINGS.md` config:

- **Project ID** (e.g., `my-gcp-project`)
  - **Cluster Name** (e.g., `my-gke-cluster`)
  - **Cluster Location** (e.g., `us-central1`)
  - **Workload Name** (e.g., `payment-api`)
  - **Workload Namespace** (e.g., `checkout`)
  - **Issue Time** (Optional, e.g., `2026-06-01T15:30:00Z`)

Before running any diagnostics or `kubectl` commands, you **must** fetch GKE credentials and context for the target GKE cluster:

```bash
gcloud container clusters get-credentials <cluster_name> --region <cluster_location>
```

#### Time Handling & Fallbacks:

1. **Determine Issue Timestamp ($T$)**:
   - **Specific Time Provided**: If the user provides a specific timestamp, use it as $T$.
…

Read the whole file at its exact version.

How to install

Latest version
mdr add gke-labs/kube-agents/gke-workload-troubleshooting@git:20260909.eb89697
Exact content
mdr add gke-labs/kube-agents/gke-workload-troubleshooting@sha256:2dd153440aa9e119

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

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Versions

versioncommittedcommitsizeaudit
git:20260909.eb89697 latest2026-09-09 eb89697 9,648 BA view · diff
git:20260904.e20318d2026-09-04 e20318d 9,482 BA view · diff
git:20260821.10730d82026-08-21 10730d8 9,472 BA view · diff
git:20260812.8e8a46c2026-08-12 8e8a46c 9,294 BA view · diff
git:20260728.aca5b5c2026-07-28 aca5b5c 9,025 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (9648 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

gke-labs/kube-agents · 64 stars · license Apache-2.0 · pushed 2026-09-23 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_iw4ag2dhz364eqdz
GET https://markdownregistry.com/api/v1/resolve?ref=gke-labs/kube-agents/gke-workload-troubleshooting
GET https://markdownregistry.com/api/v1/blob/2dd153440aa9e119b17107d9dbbf4a2de04149675aef0894527647a0989023c0

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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